Data Engineer
Core
Design, develop, and optimize large-scale data processing applications and pipelines for banking, financial, and energy clients.
Role type
Senior Data Engineer (Distributed Systems)
Builds
High-performance data pipelines processing 80–90 million records daily, Native APIs, and data services.
Domain
Financial Services, Banking, Energy
Deliverable
production ML models | product features | infrastructure
Required skills
Scala, Apache Spark, Java, distributed systems, ETL/ELT, SQL, relational/non-relational databases, performance tuning, data modeling
Preferred skills
Cloud platforms (AWS, Azure, GCP), containerized deployments, Kafka, Airflow, Hadoop ecosystem, CI/CD pipelines
Technologies
Scala, Apache Spark, Java, Kafka, Airflow, Hadoop, AWS, Azure, GCP
Responsibilities
Design and optimize large-scale data processing applications; Build and maintain high-performance data pipelines; Develop and integrate Native APIs and data services; Optimize Spark jobs and distributed computing processes; Implement best practices for data quality, monitoring, and governance; Troubleshoot performance bottlenecks in data pipelines; Participate in code reviews and architecture decisions.
